Project Background: Achieving glycemic control is the most difficult element of management for many of the estimated 1.3 million VA patients with diabetes. The VA compares favorably with the private sector based upon performance measures. However, the use of aggregate data masks inadequate glycemic control among veterans who are younger, of minority status, and/or have mental health conditions. Despite wide-spread recognition of the importance of CCI in diabetes management, it is not known how they inter-relate with demographic factors (age, sex, race) to impact medication adherence and clinical inertia that are the major mediators of glycemic control. The specific role of inertia in insulin initiation in veterans with prevalent diabetes of longer duration, as well as initiation and intensification of oral medication in veterans with more recent onset disease is also not known. Project Objectives: Our overarching aim is to evaluate the relationship between CCI, demographic factors and glycemic treatment in veterans of different age, sex and racial/ethnic groups. Our specific objectives are: (1) To evaluate how differences in CCI are related to differences in HbA1c trends for individuals with prevalent and recent-onset diabetes. (2) To evaluate how differences in CCI are related to differences in anti- glycemic treatment, including both clinical inertia (lack of medication intensification or step up in medication dose and/or new prescription when indicated) and diabetes medication non-adherence. (3) To evaluate the extent to which variation in diabetes care among racial/ethnic groups is related to differences in the presence of CCI. Project Methods: This project will be a retrospective analysis of dynamic cohorts of veterans with diabetes identified from 1999-2006, and followed through 2009. We will identify prevalent co- morbid conditions and assign them as concordant or discordant based upon a conceptual model developed by Piette and Kerr. Analyses will be conducted separately for veterans with prevalent or incident diabetes. For the first objective, the outcome will be repeated individual HbA1c measurements and we will use growth curve models (random effects) that adjust for seasonality to evaluate individual HbA1c trend (i.e., slope). Using stratification as well as regression, we will evaluate the interaction of CCI and demographic variables on the HbA1c trend. Using Cox, logistic and linear multivariable regression models, we will evaluate the relationship of CCI and race with clinical inertia and medication adherence.